systems
Agent
AI Agent
An AI that can plan and take actions, not just answer questions
Reading level
PRACTITIONER — Technical context
AI agents combine an LLM (for reasoning and planning) with tool use and a feedback loop. The agent observes its environment, reasons about what actions to take, executes tool calls (web search, code execution, API calls), observes the results, and iterates until the goal is achieved. Common frameworks: ReAct (reason+act interleaved), Plan-and-Execute, multi-agent systems with specialized sub-agents.
Real-world example
Devin (the AI software engineer) is an agent. You give it a GitHub issue, and it reads your codebase, writes code, runs tests, fixes failures, and opens a pull request — all autonomously.
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